TRAF6dn FITC-labeled peptide cultured with MM cell lines for 72 hours and monitored FITC positive MM cells using immunofluorescent microscopy (20X).

Evaluation of AKT signaling pathway in primary MM cells treated with a TRAF6dn inhibitory peptide.

Cloning of the pLenti6.2-hTRAF6dn vector. The TRAF6dn cDNA was cloned into PCRII TOPO vector to produce a 167-amino acid peptide and then sub-cloned into a pLenti6.2 expression vector (pLenti6.2-hTRAF6dn).

We hypothesized that ruxolitinib may inhibit the immune checkpoint protein, B7H3; and, thus, investigated its effects on this immune inhibitor using multiple myeloma (MM) cell lines, bone marrow (BM) mononuclear cells from MM patients and human MM LAG λ ‐1A xenografts. Ruxolitinib reduced B7H3 gene and protein expression and increased IL‐2 and CD8 gene expression. These results suggest that ruxolitinib inhibition of B7H3 may restore exhausted T‐cell activity in the MM BM tumor microenvironment.

10597 Background: Lynch syndrome (LS) is the most common cause of hereditary colorectal cancer (CRC) with an increased CRC lifetime risk of 70-80%. LS affects 1:250 individuals and is caused by pathogenic variants in the mismatch repair (MMR) genes. Statistical prediction models such as MMRpro and PREMM5 are widely used to identify LS carriers. However, these models are trained and validated in mostly white populations, and there remains a gap in understanding their performance in Hispanic populations. The purpose of this study was to evaluate the performance of MMRpro and PREMM5 on a large Hispanic cohort from the Clinical Cancer Genomics Community Research Network (CCGCRN). Methods: We validated MMRpro and PREMM5 on 3,490 CCGCRN families, of which 1,122 are Hispanic and 2,062 Non-Hispanic. The two models were evaluated for discrimination using the C-statistic, calibration using the observed to expected ratio (O/E), and overall performance using the root Brier score and negative and positive predictive value (NPV/PPV) at the 5% carrier probability threshold. Evaluations were stratified by ethnicity, and 95% confidence intervals were obtained via bootstrapping for all measures. Results: The C-statistic is 0.90 for both MMRpro (95% CI: 0.88, 0.92) and PREMM5 (95% CI: 0.87, 0.92). When stratified by ethnicity, the C-statistics are 0.96 (95% CI: 0.94, 0.97) and 0.86 (95% CI: 0.83, 0.89) for Hispanics and Non-Hispanics, respectively, in MMRpro, and 0.96 (95% CI: 0.94, 0.97) and 0.84 (95% CI: 0.79, 0.88) in PREMM5. Both models underpredict mutation probabilities, with O/E ratios ranging from 1.79 to 1.96. At a 5% threshold, variations in PPV between Hispanics and Non-Hispanics are observed in both models: 0.72 (95% CI: 0.63, 0.80) and 0.43 (95% CI: 0.37, 0.50) in Hispanic and Non-Hispanic groups in MMRpro; 0.50 (95% CI: 0.43, 0.57) and 0.25 (95% CI: 0.20, 0.30) in PREMM5. We observe less variation and higher values in NPVs in both models. Conclusions: Overall, MMRpro and PREMM5 perform well in this cohort in predicting the probability of having a pathogenic variant in an MMR gene, with modest underprediction. While these results offer reassurance for the clinical use of MMRpro and PREMM5 in Hispanic populations, further validation studies in underrepresented racial and ethnic populations are crucial.

B-cell maturation antigen (BCMA) is expressed on malignant plasma cells from patients with multiple myeloma (MM). These patients have higher levels of serum (s)BCMA than healthy subjects, and levels correlate with disease status. The half-life of sBCMA is only 24–36 h, and levels are independent of renal function. We determined whether baseline sBCMA values, a ≥ 25% increase, and a ≥ 50% decrease during treatment predicted progression-free survival (PFS) and overall survival (OS) among 81 patients with relapsed/refractory MM (RRMM) starting new treatments. Serum was obtained on day 22 of each patient’s 28-day cycle of new therapy. Kaplan–Meier survival analysis and log-rank comparison tests were used to determine the effect of baseline sBCMA. The effect of percentage change in sBCMA was investigated using time-dependent Cox proportional hazard models. Patients with baseline sBCMA levels above the median had a shorter PFS (p = 0.0077), and those in the highest quartile had a shorter PFS (p = 0.0012) and OS (p = 0.0022). A ≥ 25% increase at week 4, week 8, and anytime through week 12 predicted a shorter PFS (p = 0.0011, p = 0.0005, and p < 0.0001, respectively). A ≥ 50% decrease at week 4, week 8, and anytime through week 12 predicted a longer PFS (p = 0.0045, p = 0.029, p = 0.0055, respectively). A ≥ 25% increase in sBCMA occurred before progression according to International Myeloma Working Group criteria in 67.5% of patients. Our results indicate the potential for the use of sBCMA as a new biomarker for monitoring patients with RRMM.

Multiple myeloma (MM) patients with smoldering (S) disease are defined by a lack of CRAB/SLiM criteria but may transform into disease requiring treatment. The International Myeloma Working Group risk stratification model for SMM uses serum M‐protein, serum‐free light chain ratio, and bone marrow plasma cell percentage. We investigated whether baseline serum B‐cell maturation antigen (sBCMA) levels are predictive of disease progression among 65 patients with SMM.

SummaryThe serum B‐cell maturation antigen (sBCMA) has been identified as a novel serum biomarker for patients with multiple myeloma. However, no study has yet established a reference range for sBCMA levels. Its levels were determined in 196 healthy subjects and showed a right‐tailed distribution with a median value of 37·51 ng/ml with a standard deviation of 22·54 ng/ml (range 18·78–180·39 ng/ml). Partitioning of subgroup reference ranges was considered but determined to be irrelevant. A non‐parametric method using the median ± 2 standard deviations suggests using a universal reference interval of <82·59 ng/ml.

PURPOSE: ASCO is the premier and largest global professional society for oncology care professionals. In 2015, ASCO launched a longitudinal Learning Cohort Pilot Project to catalog and better understand the learning behaviors and preferences of oncology health care providers. A secondary goal was to assess learner preferences and utilization related to ASCO’s portfolio of educational resources. METHODS: The Learning Cohort Pilot Project was conducted between November 2015 and August 2016 with 49 ASCO members. Participants were selected via convenience sampling and stratified random sampling to generate a cohort that mirrored the demographic distribution of overall ASCO membership. Participants completed a different ASCO resource-specific feedback activity each month, which measured professional educational needs, sources sought, and preferences for educational resources. Responses were organized by demographic variables in our participant pool to identify trends in provider learning preferences. Fisher’s exact test was used to assess the association between participant demographics and practice setting and responses. Holm’s procedure was used to adjust for multiple testing. RESULTS: The Learning Cohort Pilot Project revealed statistically significant relationships between participant demographic variables and learning preferences. Age and practice setting were the demographic variables most consistently associated with the different preferences explored throughout the targeted activities. CONCLUSION: The results of this pilot cohort reinforced the hypothesis that oncology care providers have different professional educational needs and preferences that can be potentially anticipated and met with tailored resources. Delivering solutions to meet these needs represents an opportunity for further research and resource development.

Characterization of HIV viral rebound after the discontinuation of antiretroviral therapy is central to HIV cure research. We propose a parametric nonlinear mixed effects model for the viral rebound trajectory, which often has a rapid rise to a peak value followed by a decrease to a viral load set point. We choose a flexible functional form that captures the shapes of viral rebound trajectories and can also provide biological insights regarding the rebound process. Each parameter can incorporate a random effect to allow for variation in parameters across individuals. Key features of viral rebound trajectories such as viral set points are represented by the parameters in the model, which facilitates assessment of intervention effects and identification of important pretreatment interruption predictors for these features. We employ a stochastic expectation-maximization (StEM) algorithm to incorporate HIV-1 RNA values that are below the lower limit of assay quantification. We evaluate the performance of our model in simulation studies and apply the proposed model to longitudinal HIV-1 viral load data from five AIDS Clinical Trials Group treatment interruption studies.

Multiple myeloma (MM) tumour cells evade host immunity through a variety of mechanisms, which may potentially include the programmed cell death ligand-1 (PD-L1):programmed cell death protein-1 (PD-1) axis. This interaction contributes to the immunosuppressive bone marrow (BM) microenvironment, ultimately leading to reduced effector cell function. PD-L1 is overexpressed in MMBM and is associated with the resistance to immune-based approaches for treating MM. Ruxolitinib (RUX), an inhibitor of the Janus kinase (JAK) family of protein tyrosine kinases, is approved for myeloproliferative diseases. We investigated the effects of RUX alone or in combination with anti-MM agents on the expression of PD-L1 and T-cell cytotoxicity in MM. We showed that the expression of the PD-L1 gene was markedly increased in BM mononuclear cells from patients with MM with progressive disease versus those in complete remission. Furthermore, RUX treatment resulted in a concentration-dependent reduction of PD-L1 gene expression in the MM tumour cells cultured alone or co-cultured with stromal cells compared with untreated cells. The results also demonstrated that RUX increased MM cell apoptosis in the presence of interleukin-2-stimulated T cells to a similar degree as the treatment with anti-PD-1 or anti-PD-L1 antibodies. In summary, these results indicate that RUX can block PD-L1 expression resulting in augmentation of anti-MM effects of T cells.

Background: Lynch syndrome, the most common colorectal cancer (CRC) syndrome, is caused by germline mismatch repair (MMR) genes. Precise estimates of age-specific risks are crucial for sound counseling of individuals managing a genetic predisposition to cancer, but published risk estimates vary. The objective of this work is to provide gene-, sex-, and age-specific risk estimates of CRC for MMR mutation carriers that comprehensively reflect the best available data. Methods: We conducted a meta-analysis to combine risk information from multiple studies on Lynch syndrome-associated CRC. We used a likelihood-based approach to integrate reported measures of CRC risk and deconvolved aggregated information to estimate gene- and sex-specific risk. Results: Our comprehensive search identified 10 studies (8 on MLH1, 9 on MSH2, and 3 on MSH6). We estimated the cumulative risk of CRC by age and sex in heterozygous mutation carriers. At age 70 years, for male and female carriers, respectively, risks for MLH1 were 43.9% (95% confidence interval [CI] = 39.6% to 46.6%) and 37.3% (95% CI = 32.2% to 40.2%), for MSH2 were 53.9% (95% CI = 49.0% to 56.3%) and 38.6% (95% CI = 34.1% to 42.0%), and for MSH6 were 12.0% (95% CI = 2.4% to 24.6%) and 12.3% (95% CI = 3.5% to 23.2%). Conclusions: Our results provide up-to-date and comprehensive age-specific CRC risk estimates for counseling and risk prediction tools. These will have a direct clinical impact by improving prevention and management strategies for both individuals who are MMR mutation carriers and those considering testing.

Introduction: Multiple myeloma (MM) tumor cells evade host immunity through the interaction of PD-L1 and PD-L2 to PD-1 on T-cells. This creates an immunosuppressive milieu in the bone marrow (BM) microenvironment. The immune inhibitory proteins PD-L1 and PD-L2 are highly expressed in MM BM. Moreover, increased expression of these proteins are associated with resistance to treatment in MM. Ruxolitinib (RUX) is a JAK1/2 inhibitor that is effective for the treatment of myeloproliferative diseases. In this study, we examined PD-L1 and PD-L2 gene and protein expression in the BM of MM patients with progressive disease (PD) or in complete remission (CR). We further investigated the effects of RUX on expression of PD-L1 and PD-L2 in MMBM, and the effect of RUX in combination with anti-MM agents in vitro and in vivo. Material and Methods: BM mononuclear cells (MCs) and serum were collected from MM patients and healthy subjects after obtaining IRB approval. Single-cell suspensions were prepared from human MM LAGκ-1A xenografts which had been grown in the mice. The cells were cultured and treated with or without RUX and then were determined by qPCR, flow cytometric analysis, ELISA, and western blot. Results and Discussion: The results from qPCR and flow cytometric assays showed that PD-L1 and PD-L2 gene expression was markedly increased in BMMCs from MM patients with PD compared with patients in CR or with healthy controls. We further investigated the effects of RUX on PD-L1 and PD-L2 expression in primary and stromal cells from MM patients' BM samples in vitro. RUX treatment markedly reduced PD-L1and PD-L2 gene and protein expression in the MM tumor cells cultured alone or co-cultured with stromal cells in a concentration dependent pattern. We then determined whether RUX can augment the anti-MM effects of T-cells in vitro. RUX (0, 0.1, 0.5, 1, and 5 µM) increased MM cell apoptosis in the presence of IL-2 stimulated T-cells in a concentration dependent fashion, to a similar degree to anti-PD-1 (0, 0.5, 1, 5, and 10 µg/ml) or anti-PD-L1 (0, 0.5, 1, 5, and 10 µg/ml) antibody treatment. Moreover, the combination of RUX with anti-PD-1 or anti-PD-L1 antibody increased T-cell-induced MM cell apoptosis more than the agents alone. To evaluate the efficacy of drugs in vivo, severe combined immune deficient mice implanted with the human MM xenograft LAGκ-2 were treated with RUX (30mg/kg). The results showed PD-L1 expression in the xenograft was significantly decreased in RUX-treated mice compared with the untreated control group. In contrast, RUX had no effect on PD-1 expression on T-cells. Conclusion: The PD-L1/PD-1 pathway delivers inhibitory signals that regulate both peripheral and central tolerance, and inhibit anti-tumor immune-mediated responses. This study demonstrated that the JAK inhibitor RUX downregulated PD-L1 and PD-L2 expression in both MM tumor and stromal cells. We also demonstrated that RUX alone increased T-cell-induced apoptosis of MM cells; and, moreover, the combination of RUX with anti-PD-1 and anti-PD-L1 further increased apoptosis. The results suggest that JAK inhibitors may be effective for treating MM patients through their ability to reduce expression of checkpoint proteins involved in the development of immune resistance. Thus, JAK inhibitors should help overcome the immune resistance generated by these proteins for patients with this B-cell malignancy. Disclosures Chen: Oncotraker Inc: Equity Ownership. Berenson:Amgen: Consultancy, Speakers Bureau; Sanofi: Consultancy; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Incyte Corporation.: Consultancy, Research Funding; Sanofi: Consultancy; Amag: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; OncoTracker: Equity Ownership, Other: Officer; Incyte Corporation.: Consultancy, Research Funding; Janssen: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Research Funding; Amag: Consultancy, Speakers Bureau.

The Janus kinase (JAK) pathway has been shown to play key roles in the growth and resistance to drugs that develop in multiple myeloma (MM) patients. The anti-MM effects of the selective JAK1 inhibitor INCB052793 (INCB) alone and in combination with anti-MM agents were evaluated in vitro and in vivo. Significant inhibition of cell viability of primary MM cells obtained fresh from MM patients, and the MM cell lines RPMI8226 and U266, was observed with single agent INCB and was enhanced in combination with other anti-MM agents including proteasome inhibitors and glucocorticosteroids. Single-agent INCB resulted in decrease in tumor growth of the MM xenograft LAGκ-1A growing in severe combined immunodeficient mice. Mice dosed with INCB (30 mg/kg) showed significant reductions in tumor volume on days 28, 35, 42, 49, 56, and 63. Similarly, INCB at 10 mg/kg showed anti-tumor effects on days 56 and 63. Tumor-bearing mice receiving combinations of INCB with carfilzomib, bortezomib, dexamethasone, or lenalidomide showed significantly smaller tumors when compared to vehicle control and mice treated with single agents. These results provide further support for the clinical evaluation of INCB052793 alone and in combination treatment for MM patients.

PURPOSE The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the literature to understand the clinical implications of pathogenic genetic variants. We developed and evaluated two machine learning models to classify abstracts as relevant to the penetrance-risk of cancer for germline mutation carriers-or prevalence of germline genetic mutations. MATERIALS AND METHODS We conducted literature searches in PubMed and retrieved paper titles and abstracts to create an annotated data set for training and evaluating the two machine learning classification models. Our first model is a support vector machine (SVM) which learns a linear decision rule on the basis of the bag-of-ngrams representation of each title and abstract. Our second model is a convolutional neural network (CNN) which learns a complex nonlinear decision rule on the basis of the raw title and abstract. We evaluated the performance of the two models on the classification of papers as relevant to penetrance or prevalence. RESULTS For penetrance classification, we annotated 3,740 paper titles and abstracts and evaluated the two models using 10-fold cross-validation. The SVM model achieved 88.93% accuracy-percentage of papers that were correctly classified-whereas the CNN model achieved 88.53% accuracy. For prevalence classification, we annotated 3,753 paper titles and abstracts. The SVM model achieved 88.92% accuracy and the CNN model achieved 88.52% accuracy. CONCLUSION Our models achieve high accuracy in classifying abstracts as relevant to penetrance or prevalence. By facilitating literature review, this tool could help clinicians and researchers keep abreast of the burgeoning knowledge of gene-cancer associations and keep the knowledge bases for clinical decision support tools up to date.

Multiple myeloma (MM) tumor cells evade host immunity through the interaction of programmed cell death ligand 1 (PD-L1) to PD-1. This creates an immunosuppressive milieu in the bone marrow microenvironment. The immune inhibitory proteins PD-L1 are highly expressed in MM bone marrow (BM). Moreover, increased expression of this protein is associated with resistance to treatment in MM. Ruxolitinib (RUX) is an inhibitor of the Janus kinase family of protein tyrosine kinases that is effective for the treatment of myeloproliferative diseases. In this study, we investigated the effects of RUX on expression of PD-L1 in MM, and the effect of RUX in combination with anti-MM agents in vitro and in vivo. We examined PD-L1 gene expression in MM patients with progressive disease (PD) or in complete remission (CR). The results showed that PD-L1 gene expression was markedly increased in BM mononuclear cells (MCs) from MM patients with PD compared with those patients in CR or with healthy subjects using quantitative PCR and flow cytometric assay. We further investigated the effects of RUX on PD-L1 expression of primary and stromal cells from MM patients' bone marrow samples in vitro. RUX treatment markedly reduced PD-L1 gene expression in the MM tumor cells cultured alone or co-cultured with stromal cells compared with cells not treated with the JAK1/2 inhibitor in a concentration dependent pattern. Next, we determined whether RUX can augment T-cellular anti-MM effects immunotherapy potency in vitro. We used anti-PD-1 and anti-PD-L1 blocking antibodies as a positive control. The results showed that RUX (0, 0.1, 0.5, 1, and 5 μM), increased MM cell apoptosis in the presence of IL-2 stimulated T-cells in a concentration dependent fashion to a similar extent as observed with anti-PD-1 (0, 0.5, 1, 5, and 10 μg/ml) or anti-PD-L1 (0, 0.5, 1, 5, and 10 μg/ml) antibody treatment. Moreover, the combination of RUX with anti-PD-1 or anti-PD-L1 increased T-cell inducing MM cell apoptosis 5-10%. RUX had no effect on PD-1 expression on T-cells. To evaluate these drugs in vivo, the human MM xenograft LAGκ-2 model was used. The mice were then treated with RUX, the immunomodulatory agent lenalidomide (LEN) or dexamethasone (DEX) alone, doublets or the combination of all three drugs. RUX alone produced no anti-MM effects whereas the doublets showed more anti-MM effects than any single agent, and the combination of all three drugs showed the most marked anti-MM effects.

PURPOSE:Quantifying the risk of cancer associated with pathogenic mutations in germline cancer susceptibility genes-that is, penetrance-enables the personalization of preventive management strategies. Conducting a meta-analysis is the best way to obtain robust risk estimates. We have previously developed a natural language processing (NLP) -based abstract classifier which classifies abstracts as relevant to penetrance, prevalence of mutations, both, or neither. In this work, we evaluate the performance of this NLP-based procedure.MATERIALS AND METHODS:We compared the semiautomated NLP-based procedure, which involves automated abstract classification and text mining, followed by human review of identified studies, with the traditional procedure that requires human review of all studies. Ten high-quality gene-cancer penetrance meta-analyses spanning 16 gene-cancer associations were used as the gold standard by which to evaluate the performance of our procedure. For each meta-analysis, we evaluated the number of abstracts that required human review (workload) and the ability to identify the studies that were included by the authors in their quantitative analysis (coverage).RESULTS:Compared with the traditional procedure, the semiautomated NLP-based procedure led to a lower workload across all 10 meta-analyses, with an overall 84% reduction (2,774 abstracts v 16,941 abstracts) in the amount of human review required. Overall coverage was 93%-we are able to identify 132 of 142 studies-before reviewing references of identified studies. Reasons for the 10 missed studies included blank and poorly written abstracts. After reviewing references, nine of the previously missed studies were identified and coverage improved to 99% (141 of 142 studies).CONCLUSION:We demonstrated that an NLP-based procedure can significantly reduce the review workload without compromising the ability to identify relevant studies. NLP algorithms have promising potential for reducing human efforts in the literature review process.

Introduction: The JAKSTAT pathway plays a critical role in the regulation of hematopoietic pathways and immunological cytokine signaling. The JAK pathway is also involved in tumor cell proliferation and drug resistance in multiple myeloma (MM). Thus, inhibition of the JAK pathway should be a potentially effective strategy for treating MM patients. B7-H3 is an immune checkpoint protein in the B7 superfamily and has been shown overexpressed in several tumors. Immune checkpoint blockade may suppress tumor progression or enhance anti-tumor immune responses. In this study, we investigated the effects of the JAK1/2 inhibitor ruxolitinib (Rux) on B7-H3 in MM. Materials and Methods: Bone marrow mononuclear cells (BMMCs) were collected from MM patients after obtaining IRB approval. Single-cell suspensions were prepared from human MM LAGλ-1A xenografts which had been grown in severe combined immunodeficient mice. HS-5 stromal and SUP-T1 T cells were purchased from ATCC. The cells were cultured and treated with or without RUX and then subjected to qRT-PCR, flow cytometric analysis, and western blot analysis. For qRT-PCR, total RNA was extracted and applied to cDNA synthesis, followed by qPCR. Gene expression was analyzed in MM BMMCs alone or co-cultured with stromal cells or T cells with or without Rux treatment (1μM) in vitro. Results: We identified increased B7-H3 expression in MMBMMCs from patients with progressive disease (PD) patients compared to those in complete remission (CR). Rux significantly reduced B7-H3 expression in MMBMMCs in patients with PD, MM cells (U266), and BM from patients in PD when co-cultured with stromal cells (HS-5) after 48-72 hours. Rux decreased B7-H3 expression in the human MM xenograft model LAGλ-1A when cultured ex vivo. In addition, Rux suppressed B7-H3 at protein levels as shown with flow cytometric analysis and western blotting, consistent with the gene expression results. Next, we tested whether B7-H3 blockade by Rux could potentially restore exhausted T cell activity against myeloma cells in MMBM. We found that Rux can increase IL-2 and CD8 gene expression in MMBM with lower plasma percentages (< 30%) but not among those with higher plasma cell percentages (>70%). Rux also elevated IL-2 and CD8 gene expression in BM when it was cocultured with T cells (SUP-T1), suggesting Rux may mediate immunological cytokine signaling. B7-H3-neutralizing antibody increased CD8 gene expression in MMBM in vitro, suggesting that one of the mechanisms through which Rux upregulates CD8 T cells in MMBM may be via downregulation of B7-H3. Conclusion: The immune checkpoint protein B7-H3 is overexpressed in MMBM in PD compared to CR patients. The JAK1/2 inhibitor Rux can decrease B7-H3 expression and increase IL-2 and CD8 expression in BM in vitro. Our results provide evidence for Rux inhibiting the immune checkpoint protein B7-H3 which may potentially restore exhausted T-cell activity in the MMBM tumoral microenvironment. Disclosures Chen: Oncotraker Inc: Equity Ownership. Berenson:OncoTracker: Equity Ownership, Other: Officer; OncoTracker: Equity Ownership, Other: Officer; Bristol-Myers Squibb: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Incyte Corporation.: Consultancy, Research Funding; Incyte Corporation.: Consultancy, Research Funding; Takeda: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Janssen: Consultancy, Speakers Bureau; Amag: Consultancy, Speakers Bureau; Amag: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Sanofi: Consultancy; Sanofi: Consultancy.

We have previously shown that MM patients (pts) have higher levels of serum (s) BCMA than healthy subjects and these levels can be used to monitor the course of disease of MM pts. There is a need for more rapid and accurate ways to assess the efficacy of therapy (Tx) for these pts. Thus, we compared changes in levels of sBCMA, sM-protein and SFLC among MM patients undergoing new treatments.

BACKGROUND:In 2013, the American Society of Clinical Oncology (ASCO)'s Continuing Education Committee recommended establishing an interprofessional, longitudinal cohort pilot project. The main goals of the cohort were to gain feedback from oncology providers on how they use resources to address their learning needs and gain insights into the utility of different ASCO educational activities.METHODS:The ASCO Learning Cohort Pilot Project included 49 ASCO members that were representative of the overall Society membership demographics and ran from November 2015 through August 2016. Participants documented monthly learning needs and completed monthly feedback activities focused on specific ASCO educational resources.RESULTS:The Learning Cohort Pilot Project proved a viable and innovative cohort model for analyzing the learning process for oncology healthcare professionals. The development, operations, and compliance required unique infrastructure to accomplish this project. Relationships between participant demographic variables and learning preferences are reported elsewhere.CONCLUSION:The ASCO Learning Cohort Project is a unique educational project that demonstrated feasibility and has met its goals. This paper outlines the processes of establishing a learning cohort, including participant selection, project design, and participant feedback. We evaluate the project model as a means to better understand the learning needs and behaviors of oncology healthcare professionals.